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In an ever-changing visual world, animals' survival depends on their ability to perceive and respond to rapidly changing motion cues. The primary visual cortex (V1) is at the forefront of this sensory processing, orchestrating neural responses to perturbations in visual flow. However, the underlying neural mechanisms that lead to distinct cortical responses to such perturbations remain enigmatic. In this study, our objective was to uncover the neural dynamics that govern V1 neurons' responses to visual flow perturbations using a biologically realistic computational model. By subjecting the model to sudden changes in visual input, we observed opposing cortical responses in excitatory layer 2/3 (L2/3) neurons, namely, depolarizing and hyperpolarizing responses. We found that this segregation was primarily driven by the competition between external visual input and recurrent inhibition, particularly within L2/3 and L4. This division was not observed in excitatory L5/6 neurons, suggesting a more prominent role for inhibitory mechanisms in the visual processing of the upper cortical layers. Our findings share similarities with recent experimental studies focusing on the opposing influence of top-down and bottom-up inputs in the mouse primary visual cortex during visual flow perturbations.

Introduction: Virtual reality cycling (VRC) is simulated outdoor cycling with changes in scenery in virtual reality (VR) with rotating ergometer pedals. The speed at which the scenery changes, which is the visual flow velocity, can shift according to the same pedal rotation speed., Objectives: This study investigated the effects of different visual flow velocities on the psychophysiological responses of cyclists using the VRC., Methods: Participants were asked to cycle for 20 min at 30% of their maximum exercise load under four conditions: (1) bicycle ergometer without VR (control), (2) VRC at normal visual flow velocity (VRC-normal), (3) VRC at 0.5 times the visual flow velocity of VRC-normal (VRC-slow), and (4) VRC at 1.5 times the visual flow velocity of VRC-normal (VRC-fast). The order of the four conditions was randomized in a counterbalanced design. The heart rate and rating of perceived exertion were recorded during the exercise. Participants graded their enjoyment of the task using the physical activity enjoyment scale (PACES). The measured data were analyzed by comparing the visual flow velocity conditions (VRC-slow, VRC-normal, and VRC-fast), and comparing the VRC and bicycle ergometer (VRC-normal and control)., Results: A total of 24 participants were enrolled in the study. There was a significant main effect observed in the PACES score (F (2,46) =20.129, p<0.001, partial η 2 =0.467). In the post-hoc test for the PACES, significant differences were found in the following combinations: VRC-normal > VRC-slow (p=0.005); VRC-fast > VRC-normal (p=0.003); and VRC-fast > VRC-slow (p<0.001). In the modified Borg scale for lower-limb fatigue, there were significant differences in time factor (F (2,46) =134.048, p<0.001, partial η 2 =0.854) and interaction effects (F (4,92) =3.156, p=0.018, partial η 2 =0.121). In the post-hoc test for the modified Borg scale, significant trends were found in the following combinations: VRC-normal > VRC-fast (p=0.068) and VRC-slow > VRC-fast (p=0.083)., Conclusion: The results suggest that a slower visual flow velocity may reduce the enjoyment of exercise, whereas a faster visual flow velocity may make the exercise feel less fatigued and more enjoyable., Competing Interests: Human subjects: Consent was obtained or waived by all participants in this study. Ethics Committee of Nagasaki University Graduate School of Biomedical Sciences issued approval 23071304-2. This study was carried out according to the Declaration of Helsinki. Animal subjects: All authors have confirmed that this study did not involve animal subjects or tissue. Conflicts of interest: In compliance with the ICMJE uniform disclosure form, all authors declare the following: Payment/services info: All authors have declared that no financial support was received from any organization for the submitted work. Financial relationships: All authors have declared that they have no financial relationships at present or within the previous three years with any organizations that might have an interest in the submitted work. Other relationships: All authors have declared that there are no other relationships or activities that could appear to have influenced the submitted work., (Copyright © 2024, Kawaguchi et al.)

Objectives. The purpose of the analytical and research work was to develop and perform an initial assessment of the capabilities of simulation environment for modeling the Internet of Things (IoT) components and applications. The relevance of the problem is associated with the need to simplify research and testing of such systems as the field is growing. In the implementation of the simulation environment, the following goals were pursued: building a mathematical model; implementation of software, capable of running experiments on that model; providing the user with the ability to analyze results and adjust the model.Methods. Methods of simulation modeling were used.Results. Analysis of the relevance and impact of the research results has led to an appropriate example for demonstrating methods and means of solving the problem of IoT subsystems, components, and applications simulation in the proposed environment. This example has been implemented in the part of the Smart Home application model responsible for the energy efficiency optimization in residential buildings enclosed in a simulation environment based on an integrated software package consisting of the Node-RED visual tool for flow-based programming and the Yandex Cloud / Yandex IoT Core cloud service.Conclusion. A simulation model for managing energy consumption of a "smart home" was developed and implemented using the previously specified software package, including modeling time, environmental conditions, heat loss, operating modes of heating equipment and the behavior of house residents. Based on the implemented model, an initial series of simulation experiments were also carried out, on the one hand, aimed at checking some characteristics of the functionality of the developed simulation environment and the selected example for simulation of residential premises energy management. As a result of the initial experiments, the basic functionality of the integrated software package was proven and demonstrated based on the use of Node-RED and the Yandex Cloud / Yandex IoT Core cloud service for solving problems of simulation modeling of components, subsystems and applications of the Internet of things.

In the real word, we perceive our environment as a series of static and dynamic views, with viewpoint transitions providing a natural link from one static view to the next. The current research examined if experiencing such transitions is fundamental to learning the spatial layout of small-scale displays. In Experiment 1, participants viewed a tabletop array from 4 orientations in 1 of 3 conditions. The control condition presented the array sequentially, as a series of static views. In the remaining conditions, participants experienced the transition between viewpoints by rotating the array or moving around it. Both transitions improved spatial performance. Experiment 2 added a passive rotation condition to examine the effect of watching the transition without actively generating it. Spatial performance was equivalent across active and passive rotation conditions, with both outperforming static views. Together, these findings suggest that continuous visual flow is key to small-scale spatial learning.

Processing visual motion cues to interpret self-motion, the movement of others, and the environment's structure is vital to all animals, whether prey or predator. A new study in Drosophila identifies multiple pathways likely contributing to visual motion-dependent computations and behaviors., Competing Interests: Declaration of interests The authors declare no competing interests., (Copyright © 2022 Elsevier Inc. All rights reserved.)

BACKGROUND: Neural circuits allow whole-body yaw rotation to modulate vagal parasympathetic activity, which alters beat-to-beat variation in heart rate. The overall output of spinning direction, as well as vestibular-visual interactions on vagal activity still needs to be investigated. OBJECTIVE: This study investigated direction-dependent effects of visual and natural vestibular stimulation on two autonomic responses: heart rate variability (HRV) and pupil diameter. METHODS: Healthy human male subjects (n = 27) underwent constant whole-body yaw rotation with eyes open and closed in the clockwise (CW) and anticlockwise (ACW) directions, at 90°/s for two minutes. Subjects also viewed the same spinning environments on video in a VR headset. RESULTS: CW spinning significantly decreased parasympathetic vagal activity in all conditions (CW open p = 0.0048, CW closed p = 0.0151, CW VR p = 0.0019,), but not ACW spinning (ACW open p = 0.2068, ACW closed p = 0.7755, ACW VR p = 0.1775,) as indicated by an HRV metric, the root mean square of successive RR interval differences (RMSSD). There were no direction-dependent effects of constant spinning on sympathetic activity inferred through the HRV metrics, stress index (SI), sympathetic nervous system index (SNS index) and pupil diameter. Neuroplasticity in the CW eyes closed and CW VR conditions post stimulation was observed. CONCLUSIONS: Only one direction of yaw spinning, and visual flow caused vagal nerve neuromodulation and neuroplasticity, resulting in an inhibition of parasympathetic activity on the heart, to the same extent in either vestibular or visual stimulation. These results indicate that visual flow in VR can be used as a non-electrical method for vagus nerve inhibition without the need for body motion in the treatment of disorders with vagal overactivity. The findings are also important for VR and spinning chair based autonomic nervous system modulation protocols, and the effects of motion integrated VR. [ABSTRACT FROM AUTHOR]

Virtual reality (VR) technology combined with exercise, called VR exercise, is believed to have beneficial effects on mood; but VR factors contributing to improved mood remain ambiguous. The purpose of this study was to examine the effect of visual flow speed on psychophysiological responses (i.e., physiological responses, ratings of perceived exertion or RPE, and mood) to immersive VR exercise in a simulated natural environment. Eighteen male participants (M age = 23.1, SD = 1.9 years) cycled an ergometer at 80 watts for 5 minutes on three separate occasions while watching a first-person VR movie through VR goggles at three different speeds of visual flow, corresponding to 7.5 km.h−1, 15 km.h−1, and 22.5 km.h−1. The order of the three speeds was randomized in a counterbalanced design. We measured heart rate, oxygen uptake, minute ventilation, respiratory rate, and cadence during the exercise, and we recorded ratings of perceived exertion (RPE) and mood immediately after the exercise. We evaluated mood states with the Two-Dimensional Mood Scale. One-way repeated measures analysis of variance or the Friedman test revealed no significant effects on any physiological variables, RPE or cadence as a result of altered visual flow speed during VR exercise (p >.05). However, speed of visual flow significantly influenced participant ratings of Vitality (p = 0.01) and Pleasure (p = 0.02), with the faster speed resulting in a more positive mood state. As these findings showed that VR exercise with faster visual flow induced positive mood states, we recommend faster visual flow to induce better mood states in VR exercise. [ABSTRACT FROM AUTHOR]